Genomic Data Analyst Project Lead

About the Team

GENCODE is a Global Core Biodata Resource and part of Ensembl, a world-leading provider of genomics data resources and bioinformatics software. Since 2003, GENCODE has delivered foundational reference genome annotation for the human and mouse genomes, supporting users worldwide – from major international consortia to individual researchers and clinicians.

The HAVANA team forms the manual gene annotation arm of the GENCODE project, combining expert biological insight with cutting‑edge computational methods to deliver reference‑quality gene annotation used across research and clinical genomics.

We are now seeking a GENCODE Data Analyst Project Lead to guide this work into its next phase! Could this be you?

As the GENCODE Project Lead, you will lead a team of expert genomic data analysts and work closely with bioinformatics developers to integrate the latest biological knowledge, datasets, and technologies into high‑quality gene annotation. Your hands‑on scientific expertise will directly inform the development of manually supervised automated annotation pipelines that underpin GENCODE's global impact.

This is a senior scientific role combining leadership, deep biological insight, and computational fluency, with the opportunity to influence genome annotation across reference genomes and pangenomes.

• Lead, manage, and mentor a team of genomic data analysts, ensuring gene annotation meets the exceptionally high standards of the GENCODE project
• Produce and oversee manual gene and transcript annotation, contributing directly to reference‑quality datasets
• Identify opportunities to advance gene annotation using new biological insights, technologies, and emerging data types
• Design and deliver projects that integrate novel datasets into annotation workflows, working closely with bioinformatics developers
• Improve existing annotation pipelines and tools by identifying gaps, liaising with stakeholders, and driving solutions
• Collaborate across Ensembl to ensure effective presentation and dissemination of gene annotation
• Represent the group internally and externally, including at international conferences and with external collaborators
• Contribute to data analysis for publications, support experimental design, and influence downstream research
• Write reports, documentation, and peer‑reviewed publications

• PhD in genome science, molecular biology, genetics, or a related discipline
• Deep expertise in one or more of:
  • Genome annotation
  • Genome biology
  • Molecular biology
  • Comparative genomics
• Experience leading projects, teams, or large‑scale collaborations
• Confident use of genome browsers (Ensembl, UCSC, NCBI)
• Linux/Unix command line experience
• Scripting and data analysis skills
• Familiarity with bioinformatics tools and resources
• Experience working with genomic and/or omics datasets
• Transcriptomic sequencing and alignment methods
• Experimental omics data generation
• Computational analysis of omics data
• Comparative genomics and evolutionary constraint

• You are a highly motivated scientist with strong curiosity, initiative, and leadership capability. You are equally comfortable engaging with research literature, analysing genomic data, and guiding teams and collaborations.
• You will posses strong communication skills, with the ability to explain complex biological and computational concepts clearly
• A self‑starter able to manage multiple priorities and deadlines, Collaborative and effective in multidisciplinary, international teams!

• Direct experience annotating gene structure and function from omics data
• Expertise integrating diverse datasets to improve gene annotation
• Experience in collaborative omics research projects
• A publication and presentation track record
• Familiarity with large‑scale genome or pangenome initiatives
• Knowledge of non‑canonical translation (e.g. Ribo‑seq, immunopeptidomics)
• Understanding of non‑coding RNA biology and associated analysis methods

To apply:

Please submit an application with a personalised cover letter and CV. Incomplete applications will not be considered.

Hybrid Working:
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